Organisms — humans, animals and arguably even plants — have a striking ability to predict what their environment might throw at them. They use information from the past to respond to cues in the world and learn from surprises, meaning that when they encounter similar situations again in the future, they can act faster and more appropriately. In fact, this so-called predictive inference is such an important skill that it helps organisms to stay alive. But Susanne Still and Gavin Crooks think that this ability might also hold the key to understanding how all types of living systems behave efficiently in the natural world — perhaps with a little help from quantum information processing. Their work may even reshape how we think about life itself.
The idea that living organisms use predictive inference to help them perform better in the future is relatively straightforward to grasp. A more radical notion is that this process might also be present at much smaller scales, down to the molecular complexes that perform specific tasks within the cells of living organisms, or the “machinery of life” as Still, an information and computer scientist at the University of Hawaii at Manoa, refers to them. “Bio-molecular machines are the building blocks of our cells and there is evidence that they operate at very high energetic efficiency,” says Still.
Where does this efficiency come from? More.
Good question. Glad someone is asking.
This may or may not be the right direction but it sure beats Darwindunit: “Here’s the court order,” and forced funding of fake embryo drawings.
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